Detecting communities in real and complex networks is a highly contested topic in network
analysis. Although many metaheuristic-based algorithms for community detection have been …

Disease phenotypes are generally caused by the failure of gene modules which often have
similar biological roles. Through the study of biological networks, it is possible to identify the …

Multi-variable time series forecasting is one of several applications of machine learning.
Creating an artificial environment capable of replicating real-world behavior is useful for …

Bio-inspired algorithms are widely and successfully used in solving complex optimization
problems. However, a common challenge faced by these algorithms is getting stuck in local …

This paper introduces an agent-based model grounded in the ACO algorithm to investigate
the impact of partitioning ant colonies on algorithmic performance. The exploration focuses …

Given a directed graph, we present and experimentally validate new heuristics to find good
linear orderings of its vertices so to obtain Feedback Arc Sets which are minimal, ie such that …

Hybrid algorithms are powerful search algorithms obtained by the combination of
metaheuristics with other optimization techniques, although the most common hybridization …

Community Detection is one of the most investigated problems as it finds application in
many real-life areas. However, detecting communities and analysing community structure …

The paper delves into the analysis of optimization problems that involve changing problem
constraints over time and proposes a method to adapt metaheuristic algorithms for real-time …

In this paper we propose an algorithm based on the Tabu Search metaheuristic for the Map
Labeling problem, ie the relevant problem in cartography of assigning labels to specific …